EXAMINING ALGORITHMIC BIAS IN ONLINE MENTAL HEALTH RESOURCES

The virtual landscape is rapidly evolving to offer mental health support. However, these systems often depend on algorithms that can perpetuate existing societal biases. This raises a serious issue as users seeking support may encounter discriminatory outcomes based on their ethnicity, sex, or other sensitive attributes. It is essential to unpack t

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